Raising Cane's
U.S. · 973 locations

Raising Cane's operates 973 locations across the United States.

More about this list

This dataset provides the complete list of Raising Cane's store locations with verified addresses, phone numbers, and GPS coordinates sourced from official Raising Cane's systems.

973Locations
45States
14Data Fields
September 14, 2026File built

The file has all 973 locations across 45 states in one download. Building the same list by searching one area at a time tends to miss places, and a missed place looks like a gap in coverage that is not really there.

Need just some of them? Ask in your own words.

●Where the rows are

Map of where the Raising Cane's Locations are
One dot for every ZIP code with at least one location. Ask above for any part of it: a state, a city, a distance.

≡Sample Data Preview

raising-canes-stores.csvscroll →UTF-8
nameaddresscitystatezipphoneurlgeo precisioncountycounty fipsaddress qualitycountrylatitudelongitude
Raising Cane's Chicken Fingers849 East Dimond BlvdAnchorageAK99515(907) 865-3937https://locations.raisingcanes.com/ak/anchorage/849-east-dimond-blvdsourceAnchorage Municipality02020completeUS61.1449974593979-149.86630246946063
Raising Cane's Chicken Fingers780 East Altamonte DriveAltamonte SpringsFL32701(407) 452-6900https://locations.raisingcanes.com/fl/altamonte-springs/780-east-altamonte-drivesourceSeminole County12117completeUS28.66267450924318-81.36340141651262
Raising Cane's Chicken Fingers1771 Campbell LnBowling GreenKY42104(270) 904-4794https://locations.raisingcanes.com/ky/bowling-green/1771-campbell-lnsourceWarren County21227completeUS36.952464825813024-86.43174737324985
Raising Cane's Chicken Fingers950 Cornhusker RdBellevueNE68005(402) 401-6489https://locations.raisingcanes.com/ne/bellevue/950-cornhusker-rdsourceSarpy County31153completeUS41.158348962534276-95.93011689823898
Raising Cane's Chicken Fingers6240 Hamilton BoulevardAllentownPA18106(267) 742-3686https://locations.raisingcanes.com/pa/allentown/6240-hamilton-boulevardsourceLehigh County42077completeUS40.55594800000001-75.5781329
Five sample rows; the file you buy has all 14 columns.

{}What's in each row

FieldWhat it isRows filled
nameStore name and number100%
addressStreet address100%
cityCity name100%
stateTwo-letter state code100%
zip5-digit ZIP code100%
countryCountry code (US)100%
phoneStore phone number100%
latitudeGPS latitude coordinate100%
longitudeGPS longitude coordinate100%
urlUrl100%
geo_precisionHow exact the map point is: the source's own point, the street address, or the ZIP code's centre100%
countyCounty the location is in100%
county_fipsFive-digit federal code of that county100%
address_qualityWhether the street address is complete, missing a house number, or a PO box100%

Rows filled is measured on every row of the delivered file.

✓Where this data comes from

This dataset is compiled from Raising Cane's's own public store locator, the system behind the “find a store” page on their website.

September 14, 2026

File built

14 fields

Columns in the file

Fill measured

On every row of the delivered file

How we build and date every file: methodology.

Using ChatGPT, Claude or an API?

No setup needed. Ask ChatGPT or Claude your question about the Raising Cane's Locations and give it this page: it can open https://locationlists.com/find?dataset=raising-canes-stores with the filters you need and show you the count and price.

Using ChatGPT or Claude? Tell it to answer from locationlists.com/find — no account, no connector.

How assistants ask

No connector needed. Any AI assistant can answer from this site with a web link, no connector, no account: open https://locationlists.com/find with the question as query parameters.

If a question needs filtering, distance, drive time, combining lists or a price, open a /find link: either put the question itself in q=, or build the structured link. The answer does not need an API, a connector or an account.

Simplest, the question itself: https://locationlists.com/find?q=<the question in plain words>

Or set the parts yourself: https://locationlists.com/find?dataset=<slug>&state=<ST>&city=<city>&county=<county>&zip=<zip>&near=<place or zip>&radius=<miles>&drive=<minutes>&where=<column>:<op>:<value>&total=<rows>

Leave out what the question does not need. Use radius for straight-line miles or drive for minutes of driving (5 to 60), not both; near can name several places separated by | to reach from any of them. To ask about several lists at once, use datasets with two or more names, or category with a kind of business. To compare two lists, add relate=nearest and the other list with b. in front of its parameters. To count by area, use areas=county (or zip, state, metro). To keep only places whose county, ZIP code, metro area or state meets a Census figure, add area_where (for example county:population>1000000); with areas, per=100000 gives counts per 100,000 residents.

Links an assistant can open, each showing how many rows match, a few preview rows and the price for just that part:

Optional: connect for repeat use or wallet payments:

Read https://locationlists.com/skill.md and follow the instructions to connect LocationLists. Then show me the Raising Cane's Locations list.

Your assistant will walk you through setup and show you the price before you pay.

For developers

At 973 records this dataset is not sold by the row — buy the file. Without a connector, open https://locationlists.com/find?dataset=raising-canes-stores. An agent connected to https://locationlists.com/mcp can still search it, read a free sample file of up to 10 rows and buy the whole file itself. How agent purchasing works

?Frequently Asked Questions

What makes Raising Cane's's distribution model unique compared to its peers?

Raising Cane's operates 973 store locations across the US. For a brand-by-brand competitive breakdown — overlap analysis, territory density, white space mapping — our consulting team can build a custom analysis. Contact us for details.

I'm building a B2B prospect list targeting Raising Cane's stores. How is this data structured for CRM import?

Each row includes name, full address, phone, GPS coordinates, and website URL where available. Ready for Salesforce, HubSpot, or Excel. Our territory optimization service can take this further and assign balanced territories across all 973 locations.

How does Raising Cane's's geographic concentration affect market entry for a new complementary product?

The latitude/longitude data lets you see exactly where Raising Cane's is dense vs thin. Our site-selection service maps this against demographic overlays, competitor footprints, and drive-time radii to recommend market entry sequencing.

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